Hi. I want to analyze the following model with cross-sectional data only, and I am confused as to whether SEM is the appropriate method, and whether it is possible. I am testing whether the X1 predicts Y with two mediating variables, say x2 and x3. I am interested in seeing how x2 and x3 mediate the relationship btwn X1 and Y. I also want to conduct multiple group analyses to assess for moderation effects (high vs. low depression) to see if mediation effects differ. I am confused as firstly, the data is cross-sectional, and secondly, my latent variables (X1, X2 and X3) only have two indicators each (as does Y1). Is this feasible? I will have approx sample of n=160.

I'm not sure why the fact that your data are cross-sectional is a concern. Mediational analysis is typically done with cross-sectional data. The model you describe can be estimated. However, a latent variable with two indicators is not identified without borrowing information from other parts of the model. This makes the model sensitive to misspecification. Also, in my opinion a latent variable with only two indicators may not be very believable.

Thanks Linda. This is helpful. My concern with cross-sectional data stemmed from readings about the limitations of cross-sectional mediation analysis, per Cole&Maxwell Psych Methods 07, who state really need longitudinal data to assess mediation as cross-sectional analysis cannot model stable relations between variables over time. However, I was aware that most mediation analysis are conducted with cross-sectional data.